What Data for This Category Looks Like
Data sources for precious metals due diligence reports include domestic precious metals exchange market APIs, monthly industry association reports, physical warehousing ledgers, and customs import and export declarations. There are three update frequency categories: real-time market data updates every 15 minutes, industry research reports are released weekly or monthly, and physical delivery and compliance filing documents are updated irregularly. Documents mostly consist of structured tables paired with semi-structured text. Fields include product identifier, purity level, trading benchmark price, warehousing code, and compliance filing number. Mixed units are used, such as gram, ounce, kilogram, CNY per gram, and others.
What Constraints These Characteristics Impose on Vector Models and Indexes
High-frequency updates of real-time market data require indexes to support incremental writes, avoiding excessive time costs from full reconstruction. Mixed units in fields cause semantic ambiguity during vector encoding, so unit standardization processing must be completed first. The mixed structure of structured fields and semi-structured text requires indexes to support both structured metadata retrieval and full-text vector retrieval. Unique identifier fields such as compliance filing numbers need separate inverted indexes to avoid confusion with text content vectors. Wide variation in document length requires a segmentation strategy adapted to content blocks of different lengths, preventing key information loss from long text truncation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to the mixed content length of both short structured fields and long analytical paragraphs in precious metals due diligence reports, avoiding semantic fragmentation or loss of local information |
incremental_index_enable | true | Adapts to the high-frequency update requirements of precious metals real-time market data, supports incremental index writes without full reconstruction |
retrieve_top_k | Top 10–15 results | Balances retrieval recall rate and response speed, adapting to the multi-dimensional information retrieval needs of due diligence reports |
similarity_threshold | 0.75–0.85 | Filters low-correlation market or research report data, preventing irrelevant product information from being included in retrieval results |
metadata_index_fields | ["pure_rate", "trading_price", "warehouse_code"] | Creates separate inverted indexes for core structured fields in precious metals due diligence reports, improving precise retrieval efficiency |
unit_normalization_config | Enabled | Uniformly handles mixed units in precious metals fields, ensuring consistent semantics during vector encoding |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Symptom: Vector model API call returns
400 status code no body. Cause: Vector model request parameters adapted for financial scenarios are not properly configured, or precious metals data contains unstandardized special characters causing abnormal request body format. - Symptom: After upgrading to a new version, old vector database data cannot be imported normally, with a prompt indicating incompatible data format. Cause: The official provided vector database migration tool was not used, and directly copying old vector database files resulted in version format mismatch.
- Symptom: Out-of-memory errors occur when creating knowledge base vectors after local deployment, triggered at fixed times each day. Cause: Incremental index function is not enabled, concurrent write count is not limited during full indexing, and content segmentation threshold is not configured, resulting in excessively large batch processing data.
How to Confirm Proper Configuration
- Run an incremental index test: Upload a new piece of precious metals real-time market data, check whether the index is automatically updated, and confirm that no full reconstruction process is triggered.
- Retrieve precious metals data containing a specific purity level, verify that the returned results include the configured metadata fields, and that units have completed standardization conversion.
- Check the vector model call logs, confirm that the returned vector dimensions match the configured model parameters, and that there are no abnormal error messages.
- Simulate multiple concurrent retrieval requests, check whether server memory usage remains stable, and no continuous spikes occur.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.